QIRM: A quantum interactive retrieval model for session search
QIRM: A quantum interactive retrieval model for session search
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QIRM：用于会话搜索的量子交互式检索模型
DOI：
10.1016/j.neucom.2021.04.013
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发表时间：
2021-04
期刊：
影响因子：
6
通讯作者：
Yazhou Zhang
中科院分区：
文献类型：
--
作者：
Panpan Wang;Yuexian Hou;Zhao Li;Yazhou Zhang
网络搜索已经成为人们获取信息的一种流行方式。由于搜索任务的复杂性，一次检索不能满足用户的所有信息需求。需要与搜索引擎进行多次交互，会话搜索应运而生。目前提出的会话搜索方法还不能充分利用交互信息来捕捉用户的隐含信息需求。近年来，量子理论被相继应用于信息检索领域。我们发现量子测量和会话相互作用之间的相似之处。因此，本文提出了一个量子交互检索模型(QIRM)，该模型同时包括量子标准测量(QSM)和量子弱测量(QWM)，以重新刻画用户在会话交互过程中的认知变化。特别是，用户在强交互和弱交互中的认知状态被量化为分别由QSM和QWM形式化的量子表示。然后，这些表示被视为用于计算被评估文档的排名分数的用户的信息需求。我们在TREC 2013和2014年的会话轨迹数据集上进行了实验。实验结果证明了该方法的有效性，在nDCG@10和ERR@10方面获得了非常接近的性能。
Web search has become a popular way for people to obtain information. Due to the complexity of search task, one retrieval cannot serve all of user’s information needs. Multiple interactions with the search engine are required, and session search comes into being. Currently proposed session search methods still cannot take advantage of interactive information to capture the user’s implicit information needs. Recently, quantum theory has been successively applied into information retrieval task. We find the similarities between quantum measurements and session interactions. This paper thus develops a Quantum Interactive Retrieval Model (QIRM), which involves both quantum standard measurement (QSM) and quantum weak measurement (QWM) to re-characterize the user’s cognition shifts during a session interaction. Particularly, the user’s cognition states in strong interaction and weak interaction are quantified into quantum-like representations formalized by QSM and QWM, respectively. The representations are then viewed as the user’s information needs for computing ranking score of an evaluated document. We conduct experiments on TREC 2013 and 2014 Session Track datasets. The empirical evaluation demonstrates the effectiveness of our proposed methods, which obtains very comparable performance in terms of nDCG@10 and ERR@10.